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<p>The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to significant global health burden, including both acute infections and persistent post-acute sequelae, also known as Long COVID (LC) in survivors. While clinical management has reduced case-fatality rates, a substantial proportion of patients develop LC, a heterogeneous syndrome with long-term symptoms. This complex continuum requires therapeutic strategies for both the acute and chronic phases. Plasma proteomics has emerged as a powerful tool in precision medicine, offering insights into systemic molecular changes and disease trajectories. Using targeted and untargeted proteomic analyses, researchers can identify disease-relevant pathways, perform cellular deconvolution to assess tissue-specific contributions, and pinpoint therapeutic targets for both acute infection and persistent symptoms. Combined with bioinformatics and machine learning, these proteomic insights support biomarker discovery and drug repurposing strategies.</p>

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Computational proteomics to enhance personalized treatment of COVID-19 and Long COVID

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月7日

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  • Debasis Sahu,
  • Logan R. Van Nynatten,
  • David Tweddell,
  • Mark Daley,
  • Douglas D. Fraser

摘要

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to significant global health burden, including both acute infections and persistent post-acute sequelae, also known as Long COVID (LC) in survivors. While clinical management has reduced case-fatality rates, a substantial proportion of patients develop LC, a heterogeneous syndrome with long-term symptoms. This complex continuum requires therapeutic strategies for both the acute and chronic phases. Plasma proteomics has emerged as a powerful tool in precision medicine, offering insights into systemic molecular changes and disease trajectories. Using targeted and untargeted proteomic analyses, researchers can identify disease-relevant pathways, perform cellular deconvolution to assess tissue-specific contributions, and pinpoint therapeutic targets for both acute infection and persistent symptoms. Combined with bioinformatics and machine learning, these proteomic insights support biomarker discovery and drug repurposing strategies.